Intelligent driving mode selection for autonomous vehicle delivery system

ABSTRACT

The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination and selecting one of a plurality of possible routes between the origin and the destination. For each of a plurality of route segments of the selected route, mapping information is used to characterize the route segment and one of a plurality of driving modes is selected for the route segment based on the characterization of the route segment and the at least one of the item characteristic and the item identity. A driving plan comprising a collection of the selected driving modes corresponding to the plurality of route segments comprising the selected route is provided to a vehicle and the vehicle delivers the item from the origin to the destination via the selected route using the driving plan.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of and hereby incorporates byreference, for all purposes, the entirety of the contents of U.S.Nonprovisional application Ser. No. 16/797,064, filed Feb. 21, 2020, andentitled, “INTELLIGENT DRIVING MODE SELECTION FOR AUTONOMOUS VEHICLEDELIVERY SYSTEM”.

TECHNICAL FIELD OF THE DISCLOSURE

The present disclosure relates generally to autonomous vehicles (AVs)and, more specifically, to devices and methods for AV delivery drivingmode selection based on delivery contents and mapping data.

BACKGROUND

Autonomous delivery is one of the core emerging technology today, withdelivery technology changing the way the retail supply chain functions.According to a recent study, it is likely that in the near future asmany as 80% of global deliveries will be automated, as governmentscontinue to approve and adopt regulations around autonomous vehicles andpublic sentiment towards such vehicles increases.

BRIEF DESCRIPTION OF THE DRAWINGS

To provide a more complete understanding of the present disclosure andfeatures and advantages thereof, reference is made to the followingdescription, taken in conjunction with the accompanying figures, whereinlike reference numerals represent like parts, in which:

FIG. 1 is a block diagram illustrating an example autonomous vehicle inwhich an intelligent delivery system according to some embodiments ofthe present disclosure may be implemented;

FIG. 2 is a flowchart of an example method implemented by an exampleintelligent delivery system according to some embodiments of the presentdisclosure;

FIG. 3 illustrates a number of possible routes between an origin and adestination for providing a visual illustration of route segmentcondition information utilized by an intelligent delivery systemaccording to some embodiments of the present disclosure;

FIG. 4 is a flowchart of another example method implemented by anexample intelligent delivery system according to alternative embodimentsof the present disclosure;

FIG. 5 is a flowchart of yet another example method implemented by anexample intelligent delivery system according to alternative embodimentsof the present disclosure; and

FIG. 6 is a block diagram illustrating an example intelligent deliverysystem according to some embodiments of the present disclosure;

DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE DISCLOSURE

The systems, methods and devices of this disclosure each have severalinnovative aspects, no single one of which is solely responsible for theall of the desirable attributes disclosed herein. Details of one or moreimplementations of the subject matter described in this specificationare set forth in the description below and the accompanying drawings.

Fast, efficient, and safe transportation of a delivery from its point oforigin to its destination may depend on a number of factors, includingthe characteristics of the delivery itself (which may include fragile,liquid, or sturdy, for example), the condition of the road segments thatmake up the selected route (e.g., smooth, full of potholes, and/orriddled with speed bumps, and the driving behavior, or driving mode, ofthe vehicle (more or less fast, more or less aggressive, etc.).

Embodiments of the present disclosure provide a method comprisingidentifying at least one of a characteristic and an identity of an itemfor delivery from an origin to a destination and selecting one of aplurality of possible routes between the origin and the destination. Foreach of a plurality of route segments of the selected route, mappinginformation is used to characterize the route segment and one of aplurality of driving modes is selected for the route segment based onthe characterization of the route segment and the at least one of theitem characteristic and the item identity. A driving plan includes acollection of the selected driving modes corresponding to the pluralityof route segments, the driving plan comprising the selected route, isprovided to a vehicle. The vehicle delivers the item from the origin tothe destination via the selected route using the driving plan.

Embodiments of the present disclosure further provide an intelligentdelivery system for a vehicle, the intelligent delivery systemcomprising at least one sensing device for determining at least one of acharacteristic and an identity of an item for delivery from an origin toa destination via a selected route and a mapping information module forstoring mapping information including for each of a plurality of routesegments for the selected route, a characterization of the routesegment. A driving mode selection module is included for, for each ofthe plurality of route segments using the mapping information tocharacterize the route segment and selecting one of a plurality ofdriving modes for the route segment based on the characterization of theroute segment and the at least one of the item characteristic and theitem identity.

Embodiments of the present disclosure still further provide a vehiclecomprising an onboard computer; a sensor suite comprising a plurality ofimaging devices and at least one sensing device for determining at leastone of a characteristic and an identity of an item for delivery from anorigin to a destination via a selected route; and a mapping informationmodule for storing mapping information including for each of a pluralityof route segments for the selected route, a characterization of theroute segment. The vehicle further includes a driving mode selectionmodule for, for each of the plurality of route segments, using themapping information to characterize the route segment; and selecting oneof a plurality of driving modes for the route segment based on thecharacterization of the route segment and the at least one of the itemcharacteristic and the item identity.

Embodiments disclosed herein may be particularly advantageous forselecting which of a plurality of possible driving modes will be used byan AV to deliver an item, or delivery, from an origin to a destinationbased on characteristics and/or an identity of the item being deliveredand mapping data indicating a condition of various segments of aselected delivery route. Additionally, user and/or vehicle feedback maybe provided during or after the delivery and may be used to updatemapping data used in driving mode selection. Moreover, additionalconstraints and considerations, such as price charged, amount of fuelavailable or consumed, and/or amount of time to complete the deliverymay also be considered in selecting which of the plurality of possibledriving modes should be taken.

As will be appreciated by one skilled in the art, aspects of the presentdisclosure, in particular aspects of an intelligent delivery system foran autonomous vehicle, described herein, may be embodied in variousmanners (e.g., as a method, a system, a computer program product, or acomputer-readable storage medium). Accordingly, aspects of the presentdisclosure may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or an embodiment combining software and hardwareaspects that may all generally be referred to herein as a “circuit,”“module” or “system.” Functions described in this disclosure may beimplemented as an algorithm executed by one or more hardware processingunits, e.g. one or more microprocessors, of one or more computers. Invarious embodiments, different steps and portions of the steps of eachof the methods described herein may be performed by different processingunits. Furthermore, aspects of the present disclosure may take the formof a computer program product embodied in one or more computer-readablemedium(s), preferably non-transitory, having computer-readable programcode embodied, e.g., stored, thereon. In various embodiments, such acomputer program may, for example, be downloaded (updated) to theexisting devices and systems (e.g. to the existing system devices and/ortheir controllers, etc.) or be stored upon manufacturing of thesedevices and systems.

The following detailed description presents various descriptions ofspecific certain embodiments. However, the innovations described hereincan be embodied in a multitude of different ways, for example, asdefined and covered by the claims and/or select examples. In thefollowing description, reference is made to the drawings in which likereference numerals can indicate identical or functionally similarelements. It will be understood that elements illustrated in thedrawings are not necessarily drawn to scale. Moreover, it will beunderstood that certain embodiments can include more elements thanillustrated in a drawing and/or a subset of the elements illustrated ina drawing. Further, some embodiments can incorporate any suitablecombination of features from two or more drawings.

The following disclosure describes various illustrative embodiments andexamples for implementing the features and functionality of the presentdisclosure. While particular components, arrangements, and/or featuresare described below in connection with various example embodiments,these are merely examples used to simplify the present disclosure andare not intended to be limiting. It will of course be appreciated thatin the development of any actual embodiment, numerousimplementation-specific decisions must be made to achieve thedeveloper's specific goals, including compliance with system, business,and/or legal constraints, which may vary from one implementation toanother. Moreover, it will be appreciated that, while such a developmenteffort might be complex and time-consuming; it would nevertheless be aroutine undertaking for those of ordinary skill in the art having thebenefit of this disclosure.

In the Specification, reference may be made to the spatial relationshipsbetween various components and to the spatial orientation of variousaspects of components as depicted in the attached drawings. However, aswill be recognized by those skilled in the art after a complete readingof the present disclosure, the devices, components, members,apparatuses, etc. described herein may be positioned in any desiredorientation. Thus, the use of terms such as “above”, “below”, “upper”,“lower”, “top”, “bottom”, or other similar terms to describe a spatialrelationship between various components or to describe the spatialorientation of aspects of such components, should be understood todescribe a relative relationship between the components or a spatialorientation of aspects of such components, respectively, as thecomponents described herein may be oriented in any desired direction.When used to describe a range of dimensions or other characteristics(e.g., time, pressure, temperature, length, width, etc.) of an element,operations, and/or conditions, the phrase “between X and Y” represents arange that includes X and Y.

Other features and advantages of the disclosure will be apparent fromthe following description and the claims.

One embodiment is a system for autonomous vehicle delivery driving modeselection based on delivery contents and mapping data. In particular,the system enables selection of one of a plurality of possible drivingmodes that will be used by an autonomous vehicle to transport an item,or delivery, from an origin to a destination based on characteristicsand/or an identity of the item being delivered and mapping dataindicating a condition of various segments of the selected deliveryroute. Additionally, user and/or vehicle feedback may be provided duringor after the delivery and may be used to update mapping data used indriving mode selection. Moreover, additional constraints andconsiderations, such as cost, amount of fuel available or consumed,and/or amount of time to complete the delivery may also be considered inselecting one of the plurality of possible driving modes to be used.

As shown in FIG. 1 , an intelligent delivery system 100 embodyingfeatures described herein includes an autonomous vehicle 110 including apassenger interface 120, a vehicle coordinator 130, and/or a remoteexpert interface 140. In certain embodiments, the remote expertinterface 140 allows a non-passenger entity to set and/or modify thebehavior settings of the autonomous vehicle 110. The non-passengerentity may be different from the vehicle coordinator 130, which may be aserver.

A remote facility 160, which may comprise a central office or backoffice facility, may also be provided for providing the autonomousvehicle 110 (and particularly, the onboard computer 145) with a numberof different system backend functions. The remote facility 160 mayinclude one or more switches, servers, databases, live advisors, and/oran automated voice response system (“VRS”). Remote facility 160 mayinclude any or all of the aforementioned components, which may becoupled to one another via a wired or wireless local area network (LAN).Remote facility 160 may receive and transmit data via one or moreappropriate devices and network from and to the autonomous vehicle 110,such as by wireless systems, such as 882.11x, GPRS, and the like. Adatabase at the remote facility 160 can store account information suchas subscriber authentication information, vehicle identifiers, profilerecords, behavioral patterns, and other pertinent subscriberinformation. The remote facility 160 may also include a database ofroads, routes, locations, etc. permitted for use by autonomous vehicle110. The remote facility 160 may communicate with the autonomous vehicle110 to provide route guidance in response to a request received from thevehicle.

For example, based upon information stored in a mapping system of theremote facility 160, the remote facility may determine the conditions ofvarious roads or portions thereof. Autonomous vehicles, such as theautonomous vehicle 110, may, in the course of determining a navigationroute, receive instructions from the remote facility 160 regarding whichroads or portions thereof, if any, are appropriate for use under certaincircumstances, as described herein. Such instructions may be based inpart on information received from the autonomous vehicle 110 or otherautonomous vehicles regarding road conditions Accordingly, remotefacility 160 may receive information regarding the roads/routesgenerally in real-time from one or more vehicles.

The system 100 functions to enable an autonomous vehicle 110 to modifyand/or set a driving behavior in response to parameters set by vehiclepassengers (e.g., via the passenger interface 120) and/or otherinterested parties (e.g., via the vehicle coordinator 130 or remoteexpert interface 140). In accordance with features of embodimentsdescribed herein, the system 100 further functions to enable autonomousvehicle 110 to modify and/or set a driving behavior and/or routeautomatically in response to delivery contents or other considerationsor factors. Driving behavior of an autonomous vehicle may be modifiedaccording to explicit input or feedback (e.g., a passenger specifying amaximum speed or a relative comfort level), implicit input or feedback(e.g., a passenger's heart rate), or any other suitable data or mannerof communicating driving behavior preferences.

The autonomous vehicle 110 is preferably a fully autonomous automobile,but may additionally or alternatively be any semi-autonomous or fullyautonomous vehicle; e.g., a boat, an unmanned aerial vehicle, adriverless car, etc. Additionally, or alternatively, the autonomousvehicles may be vehicles that switch between a semi-autonomous state anda fully autonomous state and thus, some autonomous vehicles may haveattributes of both a semi-autonomous vehicle and a fully autonomousvehicle depending on the state of the vehicle.

The autonomous vehicle 110 preferably includes a throttle interface thatcontrols an engine throttle, motor speed (e.g., rotational speed ofelectric motor), or any other movement-enabling mechanism; a brakeinterface that controls brakes of the autonomous vehicle (or any othermovement-retarding mechanism); and a steering interface that controlssteering of the autonomous vehicle (e.g., by changing the angle ofwheels of the autonomous vehicle). The autonomous vehicle 110 mayadditionally or alternatively include interfaces for control of anyother vehicle functions; e.g., windshield wipers, headlights, turnindicators, air conditioning, etc.

In addition, the autonomous vehicle 110 preferably includes an onboardcomputer 145 and a sensor suite 150 (e.g., computer vision (“CV”)system, Light Detection And Ranging (LIDAR), RAdio Detection And Ranging(RADAR), wheel speed sensors, GPS, cameras, etc.). The onboard computer145 functions to control the autonomous vehicle 110 and processes senseddata from the sensor suite 150 and/or other sensors in order todetermine the state of the autonomous vehicle 110. Based upon thevehicle state and programmed instructions, the onboard computer 145preferably modifies or controls driving behavior of the autonomousvehicle 110.

Driving behavior, or driving mode, may include any information relatingto how an autonomous vehicle drives (e.g., actuates brakes, accelerator,steering), or a behavior of the autonomous vehicle given a set ofinstructions (e.g., a route or plan). Driving behavior may include adescription of a controlled operation and movement of an autonomousvehicle and the manner in which the autonomous vehicle applies trafficrules during one or more driving sessions. Driving behavior mayadditionally or alternatively include any information about how anautonomous vehicle calculates routes (e.g., prioritizing fastest timevs. shortest distance), other autonomous vehicle actuation behavior(e.g., actuation of lights, windshield wipers, traction controlsettings, etc.) and/or how an autonomous vehicle responds toenvironmental stimulus (e.g., how an autonomous vehicle behaves if it israining, or if an animal jumps in front of the vehicle). Some examplesof elements that may contribute to driving behavior include accelerationconstraints, deceleration constraints, speed constraints, steeringconstraints, suspension settings, routing preferences (e.g., scenic,faster routes, no highways), lighting preferences, action profiles(e.g., how a vehicle turns, changes lanes, or performs a drivingmaneuver), and action frequency constraints (e.g., how often a vehiclechanges lanes).

The onboard computer 145 functions to control the operations andfunctionality of the autonomous vehicles 110 and processes sensed datafrom the sensor suite 150 and/or other sensors in order to determinestates of the autonomous vehicles no. Based upon the vehicle state andprogrammed instructions, the onboard computer 145 preferably modifies orcontrols behavior of autonomous vehicles 110. The onboard computer 145is preferably a general-purpose computer adapted for I/O communicationwith vehicle control systems and sensor systems, but may additionally oralternatively be any suitable computing device. The onboard computer 145is preferably connected to the Internet via a wireless connection (e.g.,via a cellular data connection). Additionally or alternatively, theonboard computer 145 may be coupled to any number of wireless or wiredcommunication systems.

The sensor suite 150 preferably includes localization and drivingsensors; e.g., photodetectors, cameras, RADAR, SOund Navigation AndRanging (SONAR), LIDAR, Global Positioning System (GPS), inertialmeasurement units (IMUS), accelerometers, microphones, strain gauges,pressure monitors, barometers, thermometers, altimeters, etc.

In certain embodiments, information collected by autonomous vehicles,such as autonomous vehicle 110, may be provided to the remote facility160, which may establish a database or map of routes in a given area orregion where use of an autonomous driving system may be permitted.Information may be collected from vehicles in real-time, i.e., as thevehicle(s) traverses the route(s) in question. Information may beanalyzed by a central office of the remote facility 160 in real-time, oron a periodic basis. The information may be provided to vehiclescollectively in the area, e.g., by way of a central database or map. Forexample, vehicles may pull route information from the database/map todetermine appropriate route(s) for use of an autonomous driving systemin any manner that is convenient. In some examples, a vehicle telematicsunit may selectively communicate with the remote facility to determinewhether a route may be used with an autonomous driving system. Inaccordance with another aspect of the invention, there is provided asystem for communicating with a plurality of vehicles may include aplurality of telematics units installed into each of the vehicles. Thetelematics units are configured to collect route information as thevehicles are traveling along a vehicle route.

FIG. 2 is a flowchart of an example method 200 implemented by anintelligent delivery system according to some embodiments of the presentdisclosure. In step 202, characteristics and/or an identity of an itemfor delivery are determined. It will be recognized that this step may beperformed in any number of manners. For example, the item for deliverymay have affixed thereto a code (such as a bar code or Quick Response(QR) code, for example) or an RF ID that may be read by an appropriatesensor disposed within the vehicle. Alternatively, visual sensors, suchas a camera, may be used to discern characteristics and/or the identityof the item. Still further, information regarding characteristics and/oran identity of the item may be provided by an individual, such as asystem administrator or operator. The information gleaned in step 202may include such information as physical state of the item (e.g., solidor liquid), a durability of the item (e.g., sturdy or fragile), andwhether or not the item is perishable (and if so, within what timeframe), for example.

In step 204, a plurality of possible routes between an origin of theitem and a destination of the item may be identified using mappinginformation and one of the plurality of possible routes is selectedbased on one or more relevant factors.

In step 206, the condition of each individual segment comprising theselected route is determined and the information regardingcharacteristics and/or identity of the item as well as the condition ofthe individual segments of the selected route are evaluated to select anoptimal driving mode for the vehicle for each of the segments. Forexample, if the item being delivered is fragile (e.g., a flowerarrangement) and/or a liquid (e.g., a container of soup), and/or theparticular route segment is bumpy (e.g., full of potholes), a moreconservative (e.g., slower) driving mode may be selected for thatsegment. In contrast, if the item being delivered is sturdy and/or theparticular route segment is in good condition (e.g., smooth), a moreaggressive (e.g., faster) driving mode may be selected for that segment.For items that are neither particularly sensitive nor durable and/or aroute segment that is neither particularly bumpy nor smooth, anintermediate driving mode (e.g., intermediate speed) may be selected.

In step 208, a driving plan for the selected route is provided to thevehicle, wherein the driving plan comprises a collection of the selecteddriving modes corresponding to the individual route segments comprisingthe selected route.

FIG. 3 illustrates a number of possible routes between an origin and adestination for providing a visual illustration of route segmentcondition information utilized by an intelligent delivery systemaccording to some embodiments of the present disclosure. In particular,FIG. 3 illustrates a number of possible routes 300A-300C between anorigin 302 and a destination 304. As also shown in FIG. 3 , a number ofroute segments, e.g., segment 306, are characterized (or designated oridentified) in mapping information as “rough.” As used herein, a “rough”route segment is one that the vehicle (and passengers or contentsthereof) experiences as bumpy and/or bouncy, either constantly orintermittently, and perhaps due to potholes or other deficiencies in thesurface of the route segment or other factors. A number of other routesegments, e.g., segment 308, are characterized (or designated oridentified) in mapping information as “moderate.” As used herein, a“moderate” route segment is one that the vehicle (and passengers orcontents thereof) experiences as not particularly bumpy and/or bouncy,either constantly or intermittently, but also not particularlycomfortable due to the occasional deficiencies in the surface of theroute segment or other factors. The mapping information may includehistorical sensor data (e.g. data from vehicle suspension,accelerometers, IMUs, etc.) from vehicles previously traversing theroute segment, 3D LiDAR point-cloud data of road surfaces,approximations of road quality based thereon, user feedback fromprevious passengers of vehicles traversing the road segment, or anycombination thereof.

Finally, a number of remaining route segments, e.g., segment 310, arecharacterized (or designated or identified) in mapping information as“smooth.” As used herein, a “smooth” route segment is one that thevehicle (and passengers or contents thereof) experiences as comfortableand relatively free of bumps and/or bounces. As shown in FIG. 3 , route300A is the shortest route between the origin 302 and the destination304, but includes the highest percentage of rough segments 306 (i.e.,segments characterized as rough) of all the routes 300. Route 300C isthe longest route between the origin 302 and the designation 304, butincludes the highest percentage of smooth segments 310 (i.e., segmentscharacterized as smooth) and the lowest percentage of rough segments 306of all the routes 300. Finally, route 300B is not as short as route 300Aand not a long as 300C and the highest percentage of moderate segments308 (i.e., segments characterized as moderate) of all the routes 300.

Given the foregoing mapping information of FIG. 3 as an example, in oneembodiment, the driving plan for delivering a sturdy item from theorigin 302 to the destination 304 via the delivery route 300A would bedifferent than the driving plan for delivering a fragile item from theorigin to the destination via the same route. For example, the drivingplan for a sturdy item may include a moderately aggressive driving modefor the first segment of the route, which is indicated as being rough,and a maximally aggressive driving mode for the final segment of theroute, which is indicated as being smooth. In contrast, the driving planfor the fragile item may be include a highly conservative driving modefor the first segment of the route (rough) and a moderate or moderatelyaggressive driving mode for the final segment of the route (smooth).

Similarly, the driving plan for delivering a sturdy item from the origin302 to the destination 304 via the delivery route 300A would bedifferent than the delivery plan for delivering the same item from theorigin to the destination via the delivery route 300C. For example, incontrast to the driving plan for delivery of the sturdy item via theroute 300A, the driving plan for delivery of the sturdy item via theroute 300C may include a maximally aggressive driving mode for all butthe small segments of the route at the beginning and in the middlethereof that are indicated as being rough, for which the driving planmay include short interludes of moderately aggressive driving modes.

FIG. 4 is a flowchart of an example method 400 implemented by anintelligent delivery system according to some embodiments of the presentdisclosure. In step 402, characteristics and/or an identity of an itemfor delivery are determined. It will be recognized that this step may beperformed in any number of manners. For example, the item for deliverymay have affixed thereto a code (such as a bar code or QR code, forexample) or an RF ID that may be read by an appropriate sensor disposedwithin the vehicle. Alternatively, visual sensors, such as a camera, maybe used to discern characteristics and/or the identity of the item.Still further, information regarding characteristics and/or an identityof the item may be provided by an individual, such as a systemadministrator or operator. The information gleaned in step 402 mayinclude such information as physical state of the item (e.g., solid orliquid), a durability of the item (e.g., sturdy or fragile), and whetheror not the item is perishable (and if so, within what time frame), forexample.

In step 404, a plurality of possible routes between an origin of theitem and a destination of the item may be identified using mappinginformation and one of the plurality of possible routes is selectedbased on one or more relevant factors.

In step 406, the condition of each individual segment comprising theselected route is determined and the information regardingcharacteristics and/or identity of the item as well as the condition ofthe individual segments of the selected route are evaluated to select anoptimal driving mode for the vehicle for each of the segments. Forexample, if the item being delivered is fragile (e.g., a flowerarrangement) and/or a liquid (e.g., a container of soup), and/or theparticular route segment is bumpy (e.g., full of potholes), a moreconservative (e.g., slower, less aggressive braking and steering, etc.)driving mode may be selected for that segment. In contrast, if the itembeing delivered is sturdy and/or the particular route segment is in goodcondition (e.g., smooth), a more aggressive (e.g., faster, moreaggressive braking and steering, etc.) driving mode may be selected forthat segment. For items that are neither particularly sensitive nordurable and/or a route segment that is neither particularly bumpy norsmooth, an intermediate (e.g., moderate speed, moderately aggressivebraking and steering, etc.) driving mode may be selected.

As noted above, driving behavior, or driving mode, may include anyinformation relating to how an autonomous vehicle drives (e.g., actuatesbrakes, accelerator, steering), or a behavior of the autonomous vehicle,given a set of instructions (e.g., a route or plan). Driving behaviormay include a description of a controlled operation and movement of anautonomous vehicle and the manner in which the autonomous vehicleapplies traffic rules during one or more driving sessions. Drivingbehavior may additionally or alternatively include any information abouthow an autonomous vehicle calculates routes (e.g., prioritizing fastesttime vs. shortest distance), other autonomous vehicle actuation behavior(e.g., actuation of lights, windshield wipers, traction controlsettings, etc.) and/or how an autonomous vehicle responds toenvironmental stimulus (e.g., how an autonomous vehicle behaves if it israining, or if an animal jumps in front of the vehicle). Some examplesof elements that may contribute to driving behavior include accelerationconstraints, deceleration constraints, speed constraints, steeringconstraints, suspension settings, routing preferences (e.g., scenic,faster routes, no highways), lighting preferences, action profiles(e.g., how a vehicle turns, changes lanes, or performs a drivingmaneuver), and action frequency constraints (e.g., how often a vehiclechanges lanes).

In step 408, a driving plan for the selected route is provided to thevehicle, wherein the driving plan comprises the selected driving modesfor each of the individual route segments.

In step 410, upon completion of the delivery, information regarding theroute (e.g., actual route conditions that may include sensor data aspreviously described) and/or a condition of the item upon delivery isprovided by the vehicle and/or a user to a remote system, for example,which uses the route information to update the mapping information usedto select a route and driving mode.

FIG. 5 is a flowchart of another alternative method 500 implemented byan intelligent delivery system according to some embodiments of thepresent disclosure.

In step 502, characteristics and/or an identity of an item for deliveryare determined. It will be recognized that this step may be performed inany number of manners. For example, the item for delivery may haveaffixed thereto a code (such as a bar code or QR code, for example) oran RF ID that may be read by an appropriate sensor disposed within thevehicle. Alternatively, visual sensors, such as a camera, may be used todiscern characteristics and/or the identity of the item. Still further,information regarding characteristics and/or an identity of the item maybe provided by an individual, such as a system administrator oroperator. The information gleaned in step 502 may include suchinformation as physical state of the item (e.g., solid or liquid), adurability of the item (e.g., sturdy or fragile), and whether or not theitem is perishable (and if so, within what time frame), for example.

In step 503, additional resources and/or constraints, such as fee/price,amount of fuel required, amount of fuel available, and/or a time limitin which the delivery must be made, for example, are identified. Theseadditional resources and/or constraints may be determined based oncircumstances or imposed by a user or system operator/administrator. Forexample, a user may indicate that a particular delivery must be madewithin a certain period of time. Additionally and/or alternatively,there may only be a certain amount of fuel in the vehicle to make thedelivery and/or the delivery must be made for a particular fee.

In step 504 a plurality of possible routes between an origin of the itemand a destination of the item may be identified using mappinginformation and one of the plurality of possible routes is selectedbased on one or more relevant factors.

In step 506, the condition of each individual segment comprising theselected route is determined and the information regardingcharacteristics and/or identity of the item as well as the condition ofthe individual segments of the selected route and the additionalresources/constraints are evaluated to select an optimal driving modefor the vehicle for each of the segments. For example, if the item beingdelivered is fragile (e.g., a flower arrangement) and/or a liquid (e.g.,a container of soup), and/or the particular route segment is bumpy(e.g., full of potholes), a more conservative (e.g., slower) drivingmode may be selected for that segment. In contrast, if the item beingdelivered is sturdy and/or the particular route segment is in goodcondition (e.g., smooth), a more aggressive (e.g., faster) driving modemay be selected for that segment. For items that are neitherparticularly sensitive nor durable and/or a route segment that isneither particularly bumpy nor smooth, an intermediate driving mode(e.g., intermediate speed) may be selected.

In step 508, a driving plan for the selected route is provided to thevehicle, wherein the driving plan comprises the selected driving modesfor each of the individual route segments.

FIG. 6 is a block diagram illustrating an example system 600 that may beconfigured to implement at least portions of an intelligent deliverysystem for an autonomous vehicle, such as the autonomous vehicle 110, inaccordance with embodiments described herein, and more particularly asshown in the FIGURES described hereinabove. Part or all of theintelligent delivery system 600 may be implemented as a sensor suite,such as the sensor suite 150, and/or an onboard computer, such asonboard computer 145, and/or a remote system, such as remote facility160. As shown in FIG. 6 , the intelligent delivery system 600 mayinclude at least one processor 602, e.g. a hardware processor 602,coupled to memory elements 604 through a system bus 606. As such, thesystem may store program code and/or data within memory elements 604.Further, the processor 602 may execute the program code accessed fromthe memory elements 604 via a system bus 606. In one aspect, the systemmay be implemented as a computer that is suitable for storing and/orexecuting program code (e.g., onboard computer 145). It should beappreciated, however, that the system 600 may be implemented in the formof any system including a processor and a memory that is capable ofperforming the functions described in this disclosure.

In some embodiments, the processor 602 can execute software or analgorithm to perform the activities as discussed in this specification;in particular, activities related to an intelligent delivery system foran autonomous vehicle in accordance with embodiments described herein.The processor 602 may include any combination of hardware, software, orfirmware providing programmable logic, including by way of non-limitingexample a microprocessor, a Digital Signal Processor (DSP), afield-programmable gate array (FPGA), a programmable logic array (PLA),an integrated circuit (IC), an application specific IC (ASIC), or avirtual machine processor. The processor 602 may be communicativelycoupled to the memory element 604, for example in a direct-memory access(DMA) configuration, so that the processor 602 may read from or write tothe memory elements 604.

In general, the memory elements 604 may include any suitable volatile ornon-volatile memory technology, including double data rate (DDR) randomaccess memory (RAM), synchronous RAM (SRAM), dynamic RAM (DRAM), flash,read-only memory (ROM), optical media, virtual memory regions, magneticor tape memory, or any other suitable technology. Unless specifiedotherwise, any of the memory elements discussed herein should beconstrued as being encompassed within the broad term “memory.” Theinformation being measured, processed, tracked or sent to or from any ofthe components of the system 600 could be provided in any database,register, control list, cache, or storage structure, all of which can bereferenced at any suitable timeframe. Any such storage options may beincluded within the broad term “memory” as used herein. Similarly, anyof the potential processing elements, modules, and machines describedherein should be construed as being encompassed within the broad term“processor.” Each of the elements shown in the present figures may alsoinclude suitable interfaces for receiving, transmitting, and/orotherwise communicating data or information in a network environment sothat they can communicate with, for example, a system having hardwaresimilar or identical to another one of these elements.

In certain example implementations, mechanisms for implementing anintelligent delivery system for an autonomous vehicle as outlined hereinmay be implemented by logic encoded in one or more tangible media, whichmay be inclusive of non-transitory media, e.g., embedded logic providedin an ASIC, in DSP instructions, software (potentially inclusive ofobject code and source code) to be executed by a processor, or othersimilar machine, etc. In some of these instances, memory elements, suchas e.g. the memory elements 604 shown in FIG. 6 , can store data orinformation used for the operations described herein. This includes thememory elements being able to store software, logic, code, or processorinstructions that are executed to carry out the activities describedherein. A processor can execute any type of instructions associated withthe data or information to achieve the operations detailed herein. Inone example, the processors, such as e.g. the processor 602 shown inFIG. 6 , could transform an element or an article (e.g., data) from onestate or thing to another state or thing. In another example, theactivities outlined herein may be implemented with fixed logic orprogrammable logic (e.g., software/computer instructions executed by aprocessor) and the elements identified herein could be some type of aprogrammable processor, programmable digital logic (e.g., an FPGA, aDSP, an erasable programmable read-only memory (EPROM), an electricallyerasable programmable read-only memory (EEPROM)) or an ASIC thatincludes digital logic, software, code, electronic instructions, or anysuitable combination thereof.

The memory elements 604 may include one or more physical memory devicessuch as, for example, local memory 608 and one or more bulk storagedevices 610. The local memory may refer to RAM or other non-persistentmemory device(s) generally used during actual execution of the programcode. A bulk storage device may be implemented as a hard drive or otherpersistent data storage device. The processing system 600 may alsoinclude one or more cache memories (not shown) that provide temporarystorage of at least some program code in order to reduce the number oftimes program code must be retrieved from the bulk storage device 610during execution.

As shown in FIG. 6 , the memory elements 604 may store a driving modeselection module 620 and a mapping data module 622. In variousembodiments, the modules 620, 622, may be stored in the local memory608, the one or more bulk storage devices 610, or apart from the localmemory and the bulk storage devices. It should be appreciated that thesystem 600 may further execute an operating system (not shown in FIG. 6) that can facilitate execution of the modules 620, 622. The modules620, 622, being implemented in the form of executable program codeand/or data, can be read from, written to, and/or executed by the system600, e.g., by the processor 602. Responsive to reading from, writing to,and/or executing one of the modules 620, 622, the system 600 may beconfigured to perform one or more operations or method steps describedherein.

Input/output (I/O) devices depicted as an input device 612 and an outputdevice 614, optionally, may be coupled to the system. Examples of inputdevices may include, but are not limited to, a keyboard, a pointingdevice such as a mouse, or the like. Examples of output devices mayinclude, but are not limited to, a monitor or a display, speakers, orthe like. In some implementations, the system may include a devicedriver (not shown) for the output device 614. Input and/or outputdevices 612, 614 may be coupled to the system 600 either directly orthrough intervening I/O controllers. Additionally, sensing devices 615,may be coupled to the system 600. Examples of sensing devices 615 mayinclude, but are not limited to, cameras (located inside and/or outsidethe vehicle), LIDARs, RADARS, scales, QR code readers, bar code readers,RF sensors, and others. Sensing devices 615 may be coupled to the system600 either directly or through intervening controllers and/or drivers.

Cameras may be implemented using high-resolution imagers with fixedmounting and field of view. LIDARs may be implemented using scanningLIDARs with dynamically configurable field of view that provides apoint-cloud of the region intended to scan. RADARs may be implementedusing scanning RADARs with dynamically configurable field of view.

In an embodiment, the input and the output devices may be implemented asa combined input/output device (illustrated in FIG. 6 with a dashed linesurrounding the input device 612 and the output device 614). An exampleof such a combined device is a touch sensitive display, also sometimesreferred to as a “touch screen display” or simply “touch screen”. Insuch an embodiment, input to the device may be provided by a movement ofa physical object, such as e.g. a stylus or a finger of a user, on ornear the touch screen display.

A network adapter 616 may also, optionally, be coupled to the system 600to enable it to become coupled to other systems, computer systems,remote network devices, and/or remote storage devices throughintervening private or public networks. The network adapter may comprisea data receiver for receiving data that is transmitted by said systems,devices and/or networks to the system 600, and a data transmitter fortransmitting data from the system 600 to said systems, devices and/ornetworks. Modems, cable modems, and Ethernet cards are examples ofdifferent types of network adapter that may be used with the system 600.

Example 1 is a method including identifying at least one of acharacteristic and an identity of an item for delivery from an origin toa destination and selecting one of a plurality of possible routesbetween the origin and the destination. The method further includes, foreach of a plurality of route segments of the selected route, usingmapping information to characterize the route segment; and selecting oneof a plurality of driving modes for the route segment based on thecharacterization of the route segment and the at least one of the itemcharacteristic and the item identity. The method also includes providinga driving plan to a vehicle, wherein the driving plan comprises acollection of the selected driving modes corresponding to the pluralityof route segments comprising the selected route and wherein the vehicledelivers the item from the origin to the destination via the selectedroute using the driving plan.

In Example 2, the method of Example 1 may further include the itemcharacteristic comprising at least one of a sturdiness of the item, aphysical state of the item, and a perishability of the item.

In Example 3, the method of any of Examples 1-2 may further include theitem identity being identified by reading a code associated with theitem.

In Example 4, the method of any of Examples 1-3 may further include theitem identity being identified by information provided by a user.

In Example 5, the method of any of Examples 1-4 may further include theitem identity being identified using imaging devices to capture one ormore images of the item by which to identify the item.

In Example 6, the method of any of Examples 1-5 may further include theusing mapping information to characterize the route segment furthercomprising characterizing the route segment according to a relativecomfort level experienced by contents of the vehicle while traversingthe route segment and assigning a route type to the route segmentcorresponding to the characterization thereof.

In Example 7, the method of any of Examples 1-6 may further includesubsequent to completion of a delivery of the item, updating the mappinginformation for at least one of the plurality of route segments of theselected route using information provided by at least one of the vehicleand a vehicle passenger regarding the comfort level of the routesegment.

In Example 8, the method of any of Examples 1-7 may further includeidentifying at least one additional constraint in connection with adelivery of the item, wherein the selecting one of a plurality ofdriving modes further comprises selecting one of a plurality of drivingmodes for the route segment based on the characterization of the routesegment and the at least of the item characteristic and the itemidentity in combination with the identified at least one additionalconstraint.

Example 9 is an intelligent delivery system for a vehicle, theintelligent delivery system including at least one sensing device fordetermining at least one of a characteristic and an identity of an itemfor delivery from an origin to a destination via a selected route; amapping information module for storing mapping information including foreach of a plurality of route segments for the selected route, acharacterization of the route segment; and a driving mode selectionmodule for, for each of the plurality of route segments, using themapping information to characterize the route segment; and selecting oneof a plurality of driving modes for the route segment based on thecharacterization of the route segment and the at least one of the itemcharacteristic and the item identity.

In Example 10, the intelligent delivery system of Example 9 may furtherinclude a driving plan comprising a collection of the selected drivingmodes corresponding to the plurality of route segments comprising theselected route being provided to the vehicle.

In Example 11, the intelligent driving system of any of Examples 9-10may further include the vehicle delivering the item from the origin tothe destination via the selected route using the driving plan.

In Example 12, the intelligent delivery system of any of Examples 9-11may further include the vehicle comprising an autonomous vehicle.

In Example 13, the intelligent delivery system of any of Examples 9-12may further include the using mapping information to characterize theroute segment further comprising characterizing the route segmentaccording to a relative comfort level experienced by contents of thevehicle while traversing the route segment and assigning a route type tothe route segment corresponding to the characterization thereof.

In Example 14, the intelligent delivery system of any of Examples 9-13may further include, subsequent to completion of a delivery of the item,the mapping information for at least one of the route segments of theselected route being updated using information provided by at least oneof the vehicle and a vehicle passenger regarding the comfort level ofthe route segment.

In Example 15, the intelligent delivery system of any of Examples 9-14may further include at least one additional constraint in connectionwith a delivery of the item being identified and wherein the selectingone of a plurality of driving modes further comprises selecting one of aplurality of driving modes for the route segment based on thecharacterization of the route segment and the at least of the itemcharacteristic and the item identity in combination with the identifiedat least one additional constraint.

Example 16 is a vehicle including an onboard computer; a sensor suitecomprising a plurality of imaging devices and at least one sensingdevice for determining at least one of a characteristic and an identityof an item for delivery from an origin to a destination via a selectedroute and a mapping information module for storing mapping informationincluding for each of a plurality of route segments for the selectedroute, a characterization of the route segment. The vehicle furtherincludes a driving mode selection module for, for each of the pluralityof route segments using the mapping information to characterize theroute segment; and selecting one of a plurality of driving modes for theroute segment based on the characterization of the route segment and theat least one of the item characteristic and the item identity.

In Example 17, the vehicle of Example 16 may further include a drivingplan further comprising a collection of the selected driving modescorresponding to the plurality of route segments comprising the selectedroute is provided to the vehicle.

In Example 18, the vehicle of any of Examples 16-17 may further includethe vehicle delivering the item from the origin to the destination viathe selected route using the driving plan.

In Example 19, the vehicle of any of Examples 16-18 may further include,subsequent to completion of a delivery of the item, the mappinginformation for at least one of the route segments of the selected routebeing updated using information provided by at least one of the vehicleand a vehicle passenger regarding the comfort level of the routesegment.

In Example 20, the vehicle of any of Examples 16-19 may further include,at least one additional constraint in connection with a delivery of theitem being identified and wherein the selecting one of a plurality ofdriving modes further comprises selecting one of a plurality of drivingmodes for the route segment based on the characterization of the routesegment and the at least of the item characteristic and the itemidentity in combination with the identified at least one additionalconstraint.

It is to be understood that not necessarily all objects or advantagesmay be achieved in accordance with any particular embodiment describedherein. Thus, for example, those skilled in the art will recognize thatcertain embodiments may be configured to operate in a manner thatachieves or optimizes one advantage or group of advantages as taughtherein without necessarily achieving other objects or advantages as maybe taught or suggested herein.

In one example embodiment, any number of electrical circuits of theFIGS. may be implemented on a board of an associated electronic device.The board can be a general circuit board that can hold variouscomponents of the internal electronic system of the electronic deviceand, further, provide connectors for other peripherals. Morespecifically, the board can provide the electrical connections by whichthe other components of the system can communicate electrically. Anysuitable processors (inclusive of digital signal processors,microprocessors, supporting chipsets, etc.), computer-readablenon-transitory memory elements, etc. can be suitably coupled to theboard based on particular configuration needs, processing demands,computer designs, etc. Other components such as external storage,additional sensors, controllers for audio/video display, and peripheraldevices may be attached to the board as plug-in cards, via cables, orintegrated into the board itself. In various embodiments, thefunctionalities described herein may be implemented in emulation form assoftware or firmware running within one or more configurable (e.g.,programmable) elements arranged in a structure that supports thesefunctions. The software or firmware providing the emulation may beprovided on non-transitory computer-readable storage medium comprisinginstructions to allow a processor to carry out those functionalities.

In another example embodiment, the electrical circuits of the FIGS. maybe implemented as stand-alone modules (e.g., a device with associatedcomponents and circuitry configured to perform a specific application orfunction) or implemented as plug-in modules into application specifichardware of electronic devices. Note that particular embodiments of thepresent disclosure may be readily included in a system on chip (SOC)package, either in part, or in whole. An SOC represents an IC thatintegrates components of a computer or other electronic system into asingle chip. It may contain digital, analog, mixed-signal, and oftenradio frequency functions: all of which may be provided on a single chipsubstrate. Other embodiments may include a multi-chip-module (MCM), witha plurality of separate ICs located within a single electronic packageand configured to interact closely with each other through theelectronic package. In various other embodiments, the digital filtersmay be implemented in one or more silicon cores in Application SpecificIntegrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), andother semiconductor chips.

It is also imperative to note that all of the specifications,dimensions, and relationships outlined herein (e.g., the number ofprocessors, logic operations, etc.) have only been offered for purposesof example and teaching only. Such information may be variedconsiderably without departing from the spirit of the presentdisclosure, or the scope of the appended claims. The specificationsapply only to one non-limiting example and, accordingly, they should beconstrued as such. In the foregoing description, example embodimentshave been described with reference to particular arrangements ofcomponents. Various modifications and changes may be made to suchembodiments without departing from the scope of the appended claims. Thedescription and drawings are, accordingly, to be regarded in anillustrative rather than in a restrictive sense.

Note that with the numerous examples provided herein, interaction may bedescribed in terms of two, three, four, or more electrical components.However, this has been done for purposes of clarity and example only. Itshould be appreciated that the system can be consolidated in anysuitable manner. Along similar design alternatives, any of theillustrated components, modules, and elements of the FIGS. may becombined in various possible configurations, all of which are clearlywithin the broad scope of this Specification. In certain cases, it maybe easier to describe one or more of the functionalities of a given setof flows by only referencing a limited number of electrical elements. Itshould be appreciated that the electrical circuits of the FIGS. and itsteachings are readily scalable and can accommodate a large number ofcomponents, as well as more complicated/sophisticated arrangements andconfigurations. Accordingly, the examples provided should not limit thescope or inhibit the broad teachings of the electrical circuits aspotentially applied to a myriad of other architectures.

Note that in this Specification, references to various features (e.g.,elements, structures, modules, components, steps, operations,characteristics, etc.) included in “one embodiment”, “exampleembodiment”, “an embodiment”, “another embodiment”, “some embodiments”,“various embodiments”, “other embodiments”, “alternative embodiment”,and the like are intended to mean that any such features are included inone or more embodiments of the present disclosure, but may or may notnecessarily be combined in the same embodiments.

It is also important to note that the functions related to contactlesscurrent measurement using magnetic sensors, e.g. those summarized in theone or more processes shown in FIGS., illustrate only some of thepossible functions that may be executed by, or within, the currentmeasurement systems illustrated in the FIGS. Some of these operationsmay be deleted or removed where appropriate, or these operations may bemodified or changed considerably without departing from the scope of thepresent disclosure. In addition, the timing of these operations may bealtered considerably. The preceding operational flows have been offeredfor purposes of example and discussion. Substantial flexibility isprovided by embodiments described herein in that any suitablearrangements, chronologies, configurations, and timing mechanisms may beprovided without departing from the teachings of the present disclosure.

Numerous other changes, substitutions, variations, alterations, andmodifications may be ascertained to one skilled in the art and it isintended that the present disclosure encompass all such changes,substitutions, variations, alterations, and modifications as fallingwithin the scope of the appended claims. Note that all optional featuresof the apparatus described above may also be implemented with respect tothe method or process described herein and specifics in the examples maybe used anywhere in one or more embodiments.

In order to assist the United States Patent and Trademark Office (USPTO)and, additionally, any readers of any patent issued on this applicationin interpreting the claims appended hereto, Applicant wishes to notethat the Applicant: (a) does not intend any of the appended claims toinvoke paragraph (f) of 35 U.S.C. Section 112 as it exists on the dateof the filing hereof unless the words “means for” or “step for” arespecifically used in the particular claims; and (b) does not intend, byany statement in the Specification, to limit this disclosure in any waythat is not otherwise reflected in the appended claims.

What is claimed is:
 1. A method comprising: identifying at least one ofa characteristic and an identity of an item for delivery from an originto a destination; selecting one of a plurality of possible routesbetween the origin and the destination; for each of a plurality of routesegments of the selected route: using mapping information tocharacterize the route segment; and selecting one of a plurality ofdriving modes for the route segment based on the characterization of theroute segment and the at least one of the item characteristic and theitem identity; providing a driving plan to a vehicle, wherein thedriving plan comprises a collection of the selected driving modescorresponding to the plurality of route segments comprising the selectedroute and wherein the vehicle delivers the item from the origin to thedestination via the selected route using the driving plan; andsubsequent to completion of a delivery of the item, receivinginformation from at least one of the vehicle and a vehicle passengerregarding a comfort level of the route segment.
 2. The method of claim 1further comprising updating the mapping information for at least one ofthe route segments of the selected route using the received informationregarding the comfort level of the route segment.
 3. The method of claim1, wherein the received information comprises an indication of a levelof comfort as perceived by the vehicle passenger.
 4. The method of claim1, wherein the received information comprises sensor data indicative ofa condition of the route segment.
 5. The method of claim 1, wherein theitem characteristic comprises at least one of a sturdiness of the item,a physical state of the item, and a perishability of the item.
 6. Themethod of claim 1, wherein the item identity is identified by at leastone of reading a code associated with the item, information provided bya user, and using imaging devices to capture one or more images of theitem by which to identify the item.
 7. The method of claim 1, whereinthe using mapping information to characterize the route segment furthercomprises characterizing the route segment according to a relativecomfort level experienced by contents of the vehicle while traversingthe route segment and assigning a route type to the route segmentcorresponding to the characterization thereof.
 8. The method of claim 1further comprising identifying at least one additional constraint inconnection with a delivery of the item, wherein the selecting one of aplurality of driving modes further comprises selecting one of aplurality of driving modes for the route segment based on thecharacterization of the route segment and the at least of the itemcharacteristic and the item identity in combination with the identifiedat least one additional constraint.
 9. An intelligent delivery systemfor a vehicle, the intelligent delivery system comprising: at least onesensing device for determining at least one of a characteristic and anidentity of an item for delivery from an origin to a destination via aselected route; a mapping information module comprising at least onenon-transitory computer readable medium for storing mapping informationincluding for each of a plurality of route segments for the selectedroute, a characterization of the route segment; and a driving modeselection module comprising at least one non-transitory computerreadable medium for, for each of the plurality of route segments: usingthe mapping information to characterize the route segment; and selectingone of a plurality of driving modes for the route segment based on thecharacterization of the route segment and the at least one of the itemcharacteristic and the item identity; wherein, subsequent to completionof a delivery of the item, the mapping information for at least one ofthe route segments of the selected route is updated using informationprovided by at least one of the vehicle and a vehicle passengerregarding the comfort level of the route segment.
 10. The intelligentdelivery system of claim 9, wherein a driving plan comprising acollection of the selected driving modes corresponding to the pluralityof route segments comprising the selected route is provided to thevehicle.
 11. The intelligent delivery system of claim 10, wherein thevehicle delivers the item from the origin to the destination via theselected route using the driving plan.
 12. The intelligent deliverysystem of claim 9, wherein the vehicle comprises an autonomous vehicle.13. The intelligent delivery system of claim 9, wherein the usingmapping information to characterize the route segment further comprisescharacterizing the route segment according to a relative comfort levelexperienced by contents of the vehicle while traversing the routesegment and assigning a route type to the route segment corresponding tothe characterization thereof.
 14. The intelligent delivery system ofclaim 9, wherein at least one additional constraint in connection with adelivery of the item is identified and wherein the selecting one of aplurality of driving modes further comprises selecting one of aplurality of driving modes for the route segment based on thecharacterization of the route segment and the at least of the itemcharacteristic and the item identity in combination with the identifiedat least one additional constraint.
 15. A vehicle comprising: an onboardcomputer; a sensor suite comprising a plurality of imaging devices andat least one sensing device for determining at least one of acharacteristic and an identity of an item for delivery from an origin toa destination via a selected route; a mapping information modulecomprising at least one non-transitory computer readable medium forstoring mapping information including for each of a plurality of routesegments for the selected route, a characterization of the routesegment; and a driving mode selection module comprising at least onenon-transitory computer readable medium for, for each of the pluralityof route segments: using the mapping information to characterize theroute segment; and selecting one of a plurality of driving modes for theroute segment based on the characterization of the route segment and theat least one of the item characteristic and the item identity; wherein,subsequent to completion of a delivery of the item, the mappinginformation for at least one of the route segments of the selected routeis updated using information regarding the comfort level of the routesegment.
 16. The vehicle of claim 15, wherein a driving plan comprisinga collection of the selected driving modes corresponding to theplurality of route segments comprising the selected route is provided tothe vehicle.
 17. The vehicle of claim 16, wherein the vehicle deliversthe item from the origin to the destination via the selected route usingthe driving plan.
 18. The vehicle of claim 15, wherein the informationregarding the comfort level of the route segment comprises an indicationof a level of comfort as perceived by the vehicle passenger.
 19. Thevehicle of claim 15, wherein the information regarding the comfort levelof the route segment comprises sensor data indicative of a condition ofthe route segment.
 20. The vehicle of claim 16, wherein at least oneadditional constraint in connection with a delivery of the item isidentified and wherein the selecting one of a plurality of driving modesfurther comprises selecting one of a plurality of driving modes for theroute segment based on the characterization of the route segment and theat least of the item characteristic and the item identity in combinationwith the identified at least one additional constraint.